Delirium is a neuropsychiatric syndrome with a multifactorial etiology that occurs in a majority of ICU (Intensive Care Unit) patients. Delirium is associated with increased mortality, prolonged hospital stay, and long term effects such as decreased independent living, increased rate of institutionalization and increased risk to develop long-term cognitive impairment. Longer hospital stay and complications associated with delirium in the ICU lead to significantly higher costs of care. The prevalence rates of delirium in an ICU range from 11% to 87%. Accurate and early detection and treatment of delirium is the key to improving patient outcome and curbing delirium-related health care costs.
Currently, for the diagnosis of delirium in ICU patients a couple of validated screening questionnaires (such as CAM-ICU) are used. With these methods patients are checked at most three times a day. With the fluctuating character of delirium the delirious episodes are easily missed. Besides, under-detection of delirium is still the case even if screening instruments are used. Accurate and early detection methods may lead to more effective application of appropriate clinical interventions, leading to better outcome and reduced induced mortality. Hence, there is a need for a (semi-)automated, continuous and objective delirium monitoring system and method.
A disturbed motor activity pattern is a frequent manifested feature in delirious patients. Based on motoric alterations three clinical subtypes of delirium are distinguished: hyperactive, hypoactive and mixed. The definitions of the hypoactive, hyperactive and mixed motor subtypes are based on different psychomotor symptoms. A hyperactive delirium is characterized by increased quantity of motor activity, loss of control of activity, restlessness, and wandering. Patients with a hypoactive delirium demonstrate features such as decreased amount of activity, and decreased speed of actions. Patients with a mixed delirium shift between hypo- and hyperactivity.
Measurement of disturbed motor activity patterns to detect delirium is reported in a few studies. In these studies on-body accelerometer-based techniques were used to measure activity. Results showed that measurement of motoric alterations is a potential candidate for delirium detection.
The use of video monitoring for whole body motion detection was recently demonstrated by comparing video and wrist actigraphy for monitoring body movement in healthy subjects during sleep (Heinrich, A., van Vugt, H., A new video actigraphy method for non-contact analysis of body movement during sleep (2010), European Sleep Research Society ESRS, Journal on Sleep Research, vol. 19 (suppl. 2)). Motion data of both techniques corresponded for small, medium and large motions. Small and sometimes even medium movements were missed by conventional wrist actigraphy if the moving body part was not the one with the attached actigraphy system.
A disadvantage of wrist actigraphy methods is that it is measures the movements of the part of the body where it is attached to. So movements of other parts of the body are missed. Changes in motoric behavior are not limited to one part of the body, measurement of only one extremity might result in missed motions and as a consequence under-detection of delirium. Further, an extra on-body sensor might irritate or confuse patients.